U.S. patent number 10,372,757 [Application Number 14/883,295] was granted by the patent office on 2019-08-06 for search media content based upon tempo.
This patent grant is currently assigned to SPOTIFY AB. The grantee listed for this patent is Spotify AB. Invention is credited to Dariusz Dziuk, Tristan Jehan, Rahul Sen, Nikolaos Toumpelis.
United States Patent |
10,372,757 |
Jehan , et al. |
August 6, 2019 |
Search media content based upon tempo
Abstract
A media system includes: media-playback device including: a
media-output device that plays media content items; and a tempo
control engine configured to: receive a selection of a desired
tempo; and suggest additional media content associated with the
desired tempo.
Inventors: |
Jehan; Tristan (Brooklyn,
NY), Dziuk; Dariusz (Stockholm, SE), Sen;
Rahul (Stockholm, SE), Toumpelis; Nikolaos
(Stockholm, SE) |
Applicant: |
Name |
City |
State |
Country |
Type |
Spotify AB |
Stockholm |
N/A |
SE |
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Assignee: |
SPOTIFY AB (Stockholm,
SE)
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Family
ID: |
57324566 |
Appl.
No.: |
14/883,295 |
Filed: |
October 14, 2015 |
Prior Publication Data
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Document
Identifier |
Publication Date |
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US 20160342295 A1 |
Nov 24, 2016 |
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Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
Issue Date |
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62163927 |
May 19, 2015 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G06F
16/683 (20190101) |
Current International
Class: |
G06F
16/683 (20190101) |
References Cited
[Referenced By]
U.S. Patent Documents
Foreign Patent Documents
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1 705 588 |
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Sep 2006 |
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EP |
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1821309 |
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Aug 2007 |
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EP |
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2006/072961 |
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Jul 2006 |
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WO |
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2014/096832 |
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Jun 2014 |
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WO |
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Other References
US. Appl. No. 14/883,252, filed Oct. 14, 2015 for "Repetitive
Motion Activity Enhancement Based Upon Media Content Selection".
cited by applicant .
U.S. Appl. No. 14/883,245, filed Oct. 14, 2015 for "Heart Rate
Control Based Upon Media Content Selection". cited by applicant
.
U.S. Appl. No. 14/883,232, filed Oct. 14, 2015 for "Cadence
Determination and Media Content Selection". cited by applicant
.
U.S. Appl. No. 14/883,298, filed Oct. 14, 2015 for "Cadence-Based
Playlists Management System". cited by applicant .
U.S. Appl. No. 14/883,273, filed Oct. 14, 2015 for "Multi-Track
Playback of Media Content During Repetitive Motion Activities".
cited by applicant .
U.S. Appl. No. 14/883,318, filed Oct. 14, 2015 for "Cadence and
Media Content Phase Alignment". cited by applicant .
U.S. Appl. No. 14/944,972, filed Nov. 18, 2015 for "System for
Managing Transitions Between Media Content Items". cited by
applicant .
U.S. Appl. No. 14/945,008, filed Nov. 18, 2015 for "Identifying
Media Content". cited by applicant .
U.S. Appl. No. 14/883,323, filed Oct. 14, 2015 for "Accessibility
Management System for Media Content Items". cited by applicant
.
U.S. Appl. No. 14/883,336, filed Oct. 14, 2015 for "Selection and
Playback of Song Versions Using Cadence". cited by applicant .
U.S. Appl. No. 14/883,340, filed Oct. 14, 2015 for "Cadence-Based
Selection, Playback, and Transition Between Song Versions". cited
by applicant .
International Search Report and Written Opinion from International
Patent Application No. PCT/US2017/036575, dated Jul. 17, 2017.
cited by applicant .
The Echonest, "Analyzer Documentation", Version 3.2, Jan. 7, 2014,
7 pages. cited by applicant .
Extended European Search Report for European Patent Application No.
16169963.2, dated Oct. 21, 2016, 9 pages. cited by applicant .
Geoffray Bonnin et al: "Automated Generation of Music Playlists:
Survey and Experiments", ACM Computing Surveys., vol. 47, No. 2,
Nov. 12, 2014 (Nov. 12, 2014), pp. 1-35. cited by applicant .
Summons to Attend Oral Proceedings from the European Patent Office
for European Application No. 16169963.2, dated Oct. 31, 2017, 10
pages. cited by applicant .
International Search Report and Written Opinion from International
Patent Application No. PCT/US2017/036571, dated Aug. 4, 2017. cited
by applicant.
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Primary Examiner: Ng; Amy
Assistant Examiner: Wong; William
Attorney, Agent or Firm: Merchant & Gould P.C.
Parent Case Text
CROSS-REFERENCE TO RELATED APPLICATION
This application claims priority to U.S. Ser. No. 62/163,927, filed
on May 19, 2015, entitled SEARCH MEDIA CONTENT BASED UPON TEMPO,
and which application is hereby incorporated by reference in its
entirety.
Claims
What is claimed is:
1. A media system comprising: at least one processor; and at least
one non-transitory computer-readable data storage device storing
data instructions that, when executed by the at least one
processor, cause the media system to: receive a selected tempo
corresponding to a cadence of a repetitive-motion activity;
identify a first set of media content comprising a plurality of
media content items based upon at least a first range encompassing
the selected tempo and a first threshold for a runnability score
associated with each of the plurality of media content items,
wherein the runnability score is computed by a runnability model,
the runnability model being trained from a plurality of positive
example media content items to consider characteristics including
at least a beat strength and a tempo regularity, and the
runnability model computes the runnability score at least based on
one or more similarities between each of the plurality of media
content items and the plurality of positive example media content
items, and wherein the first threshold is decreased for media
content items previously liked by a user of the media system;
determine whether the first set contains at least a particular
number of media content items; and when a determination is made
that the first set does not contain at least the particular number
of media content items: expand the first range to determine a
second range encompassing the selected tempo; identify, based on
the second range, additional media content to generate a second set
of media content; add the second set of media content to the first
set of media content; and provide the first set of media content
and the second set of media content for playback during the
repetitive-motion activity.
2. The system of claim 1, wherein the media system further
comprises a server including the at least one processor.
3. The system of claim 1, wherein the media system uses the first
threshold to filter the runnability score to identify the first set
of media content, and a second threshold to filter the runnability
score to identify the additional media content to generate the
second set of media content, wherein the second threshold is less
than the first threshold.
4. The system of claim 1, wherein the second range of tempos is
larger than the first range of tempos.
5. The system of claim 1, wherein the media system uses
repetitive-motion activity media metadata to identify portions of
media content items suited for playback during a repetitive-motion
activity.
6. A media system, comprising: a media-playback device configured
to receive a selection of a tempo corresponding to a cadence of a
repetitive-motion activity of a user; and a server comprising at
least one processor; and at least one non-transitory
computer-readable data storage device storing data instructions
that, when executed by the at least one processor, cause the server
to: receive a selected tempo corresponding to a cadence of a
repetitive-motion activity; identify a first set of media content
comprising a plurality of media content items based upon at least a
first range encompassing the selected tempo and a first threshold
for a runnability score associated with each of the plurality of
media content items, wherein the runnability score is computed by a
runnability model, the runnability model being trained from a
plurality of positive example media content items to consider
characteristics including at least a beat strength and a tempo
regularity, and the runnability model computes the runnability
score at least based on one or more similarities between each of
the plurality of media content items and the plurality of positive
example media content items, and wherein the first threshold is
decreased for media content items previously liked by a user of the
media system; determine whether the first set contains at least a
particular number of media content items; and when a determination
is made that the first set does not contain at least the particular
number of media content items: expand the first range to determine
a second range encompassing the selected tempo; identify, based on
the second range, additional media content to generate a second set
of media content; add the second set of media content to the first
set of media content; and provide the first set of media content
and the second set of media content to the media-playback device
for playback during the repetitive-motion activity.
7. The system of claim 6, wherein the server is programmed to
identify the first set of media content by filtering a plurality of
the media content items based upon one or more criteria including
at least the first range encompassing the selected tempo and the
first threshold for the runnability score.
8. The system of claim 6, wherein the server uses the first
threshold to filter the runnability score to identify the first set
of media content, and a second threshold to filter the runnability
score to identify the additional media content to generate the
second set of media content, wherein the second threshold is less
than the first threshold.
9. The system of claim 6, wherein the second range of tempos is
larger than the first range of tempos.
10. A method for selecting media content based upon a tempo
corresponding to a cadence of a repetitive-motion activity of a
user, the method comprising: receiving a selected tempo
corresponding to a cadence of the repetitive-motion activity;
identifying a first set of media content comprising a plurality of
media content items based upon at least a first range encompassing
the selected tempo and a first threshold for a runnability score
associated with each of the plurality of media content items,
wherein the runnability score is computed by a runnability model,
the runnability model being trained from a plurality of positive
example media content items to consider characteristics including
at least a beat strength and a tempo regularity, and the
runnability model computes the runnability score at least based on
one or more similarities between each of the plurality of media
content items and the plurality of positive example media content
items, and wherein the first threshold is decreased for media
content items previously liked by a user of the media system;
determining whether the first set contains at least a particular
number of media content items; and when a determination is made
that the first set does not contain at least the particular number
of media content items: expanding the first range to determine a
second range encompassing the selected tempo; identifying, based on
the second range, additional media content to generate a second set
of media content; add the second set of media content to the first
set of media content; and providing the first set of media content
and the second set of media content for playback during the
repetitive-motion activity.
11. The method of claim 10, wherein identifying the first set of
media content includes: filtering the plurality of media content
items to identify media content items having tempos falling within
the first range of tempos.
12. The method of claim 11, wherein identifying the first set of
media content further includes filtering the plurality of media
content items based upon the first threshold for the runnability
score associated with each of the plurality of media content
items.
13. The method of claim 12, further comprising relaxing the
filtering of the plurality of media content items when identifying
the additional media content to generate the second set of media
content.
14. A media system, comprising: a server comprising at least one
processor; and at least one non-transitory computer-readable data
storage device storing data instructions that, when executed by the
at least one processor, cause the server to: receive a selected
tempo corresponding to a cadence of a repetitive-motion activity
from a media-playback device; identify a first set of media content
comprising a plurality of media content items based on at least the
selected tempo and a first threshold for a runnability score
associated with each media content item, the runnability score
being computed by a runnability model, the runnability model being
trained by a plurality of positive example media content items to
consider characteristics including at least a beat strength and a
tempo regularity, and the runnability model computes the
runnability score at least based on one or more similarities
between each media content item and the plurality of positive
example media content items, and wherein the first threshold is
decreased for media content items previously liked by a user of the
media system; determine whether the first set contains at least a
particular number of media content items; and when a determination
is made that the first set does not contain at least the particular
number of media content items: identify additional media content to
generate a second set of media content using a second threshold for
the runnability score, the second threshold for the runnability
score being less than the first threshold for the runnability
score; add the second set of media content to the first set of
media content; and provide the first set of media content and the
second set of media content to the media-playback device for
playback during the repetitive-motion activity.
Description
BACKGROUND
Running, as well as many other recreation or fitness activities,
include repetitive motions. For example, running and walking
involve repetitive steps, biking involves repetitive rotational
movements, rowing involves repetitive strokes, and swimming
involves repetitive strokes and kicks. There are of course many
other recreation and fitness activities that also include various
repetitive motions. These repetitive motion activities may be
performed in place (e.g., using a treadmill, stationary bike,
rowing machine, swimming machine, etc.) or in motion (e.g., on
roads, trails, or tracks or in a pool or body of water, etc.).
Cadence refers to the frequency of these repetitive motions and is
often measured in terms of motions per minute (e.g., steps per
minute, rotations per minute, strokes per minute, or kicks per
minute).
Many people enjoy consuming media content, such as listening to
audio content or watching video content, while running or engaging
in other repetitive-motion activities. Examples of audio content
include songs, albums, podcasts, audiobooks, etc. Examples of video
content include movies, music videos, television episodes, etc.
Using a mobile phone or other media-playback device a person can
access large catalogs of media content. For example, a user can
access an almost limitless catalog of media content through various
free and subscription-based streaming services. Additionally, a
user can store a large catalog of media content on his or her
mobile device.
This nearly limitless access to media content introduces new
challenges for users. For example, it may be difficult to find or
select the right media content that complements a particular moment
during a run or other repetitive-motion activity.
SUMMARY
In general terms, this disclosure is directed to a system for
searching for media content of a desired tempo. Various aspects are
described in this disclosure, which include, but are not limited
to, the following aspects.
In one aspect, a media system includes: media-playback device
including: a media-output device that plays media content items;
and a tempo control engine configured to: receive a selection of a
desired tempo; and suggest additional media content associated with
the desired tempo.
In another aspect, a media system includes: media-playback device
including a media-output device that plays media content items, and
a tempo control engine configured to receive a selection of a
desired tempo; and a server configured to filter a plurality of
media content items to suggest one or more suggested media content
items based upon the desired tempo provided by the media-playback
device.
In yet another aspect, a method for selecting media content based
upon tempo includes: receiving a selected tempo; identifying
additional media content based upon the selected tempo; and
providing the additional media content to a user.
BRIEF DESCRIPTION OF THE DRAWINGS
FIG. 1 illustrates an example system for tempo searching and media
content selection.
FIG. 2 is a schematic illustration of the example system of FIG.
1.
FIG. 3 illustrates an example method of selecting media content
based upon tempo by some embodiments of the media-delivery system
of FIG. 2.
FIG. 4 illustrates an example method for analyzing the tempo of
media content per the method shown in FIG. 3.
FIG. 5 illustrates an example method of filtering media content
based upon criteria per the method shown in FIG. 4.
FIG. 6 illustrates another example method of filtering media
content based upon criteria per the method shown in FIG. 5.
FIG. 7 shows an example tempo-based content playback screen
displayed by some embodiments of the user interface of FIG. 2.
FIG. 8 illustrates an example method of acquiring a list of
positive examples of runnable media content items.
FIG. 9 illustrates an example method of building a runnability
model based on positive examples of runnable media content
items.
DETAILED DESCRIPTION
Various embodiments will be described in detail with reference to
the drawings, wherein like reference numerals represent like parts
and assemblies throughout the several views. Reference to various
embodiments does not limit the scope of the claims attached hereto.
Additionally, any examples set forth in this specification are not
intended to be limiting and merely set forth some of the many
possible embodiments for the appended claims.
Users of media-playback devices often consume media content while
engaging in various activities, including repetitive motion
activities. As noted above, examples of repetitive-motion
activities may include swimming, biking, running, rowing, and other
activities. Consuming media content may include one or more of
listening to audio content, watching video content, or consuming
other types of media content. For ease of explanation, the
embodiments described in this application are presented using
specific examples. For example, audio content (and in particular
music) is described as an example of one form of media consumption.
As another example, running is described as one example of a
repetitive-motion activity. However, it should be understood that
the same concepts are equally applicable to other forms of media
consumption and to other forms of repetitive-motion activities, and
at least some embodiments include other forms of media consumption
and/or other forms of repetitive-motion activities.
The users may desire that the media content fits well with the
particular repetitive-motion activity. For example, a user who is
running may desire to listen to music with a beat that corresponds
to the user's cadence. Beneficially, by matching the beat of the
music to the cadence, the user's performance or enjoyment of the
repetitive-motion activity may be enhanced. This desire cannot be
met with traditional media-playback devices and media-delivery
systems.
FIG. 1 illustrates an example system 100 for cadence determination
and media content selection. The example system 100 includes a
media-playback device 102 and a media-delivery system 104. The
system 100 communicates across a network 106. Also shown, is a user
U who is running. The user U's upcoming steps S are shown as well.
A step represents a single strike of the runner's foot upon the
ground.
The media-playback device 102 operates to play media content items
to produce media output 110. In some embodiments, the media content
items are provided by the media-delivery system 104 and transmitted
to the media-playback device 102 using the network 106. A media
content item is an item of media content, including audio, video,
or other types of media content, which may be stored in any format
suitable for storing media content. Non-limiting examples of media
content items include songs, albums, music videos, movies,
television episodes, podcasts, other types of audio or video
content, and portions or combinations thereof.
The media-playback device 102 plays media content for the user
based on the user's cadence. In the example shown, the media output
110 includes music with a tempo that corresponds to the user's
cadence. The tempo (or rhythm) of music refers to the frequency of
the beat and is typically measured in beats per minute (BPM). The
beat is the basic unit of rhythm in a musical composition (as
determined by the time signature of the music). Accordingly, in the
example shown, the user U's steps occur at the same frequency as
the beat of the music.
For example, if the user U is running at a cadence of 180 steps per
minute, the media-playback device 102 may play a media content item
having a tempo equal to or approximately equal to 180 BPM. In other
embodiments, the media-playback device 102 plays a media content
item having a tempo equal or approximately equal to the result of
dividing the cadence by an integer such as a tempo that is equal to
or approximately equal to one-half (e.g., 90 BPM when the user is
running at a cadence of 180 steps per minute), one-fourth, or
one-eighth of the cadence. Alternatively, the media-playback device
102 plays a media content item having a tempo that is equal or
approximately equal to an integer multiple (e.g., 2.times.,
4.times., etc.) of the cadence. Further, in some embodiments, the
media-playback device 102 operates to play multiple media content
items including one or more media content items having a tempo
equal to or approximately equal to the cadence and one or more
media content items have a tempo equal or approximately equal to
the result of multiplying or dividing the cadence by an integer.
Various other combinations are possible as well.
In some embodiments, the media-playback device 102 operates to play
music having a tempo that is within a predetermined range of a
target tempo. In at least some embodiments, the predetermined range
is plus or minus 2.5 BPM. For example, if the user U is running at
a cadence of 180 steps per minute, the media-playback device 102
operates to play music having a tempo of 177.5-182.5 BPM.
Alternatively, in other embodiments, the predetermined range is
itself in a range from 1 BPM to 10 BPM.
Further, in some embodiments, the media-playback device 102
operates to play music having a tempo equal to or approximately
equal to a user U's cadence after it is rounded. For example, the
cadence may be rounded to the nearest multiple of 2.5, 5, or 10 and
then the media-playback device 102 plays music having a tempo equal
to or approximately equal to the rounded cadence. In yet other
embodiments, the media-playback device 102 uses the cadence to
select a predetermined tempo range of music for playback. For
example, if the user U's cadence is 181 steps per minute, the
media-playback device 102 may operate to play music from a
predetermined tempo range of 180-184.9 BPM; while if the user U's
cadence is 178 steps per minute, the media-playback device 102 may
operate to play music from a predetermined tempo range of 175-179.9
BPM.
FIG. 2 is a schematic illustration of an example system 100 for
cadence determination and media content selection. In FIG. 2, the
media-playback device 102, the media-delivery system 104, and the
network 106 are shown. Also shown are the user U and a satellite
S.
As noted above, the media-playback device 102 operates to play
media content items. In some embodiments, the media-playback device
102 operates to play media content items that are provided (e.g.,
streamed, transmitted, etc.) by a system external to the
media-playback device such as the media-delivery system 104,
another system, or a peer device. Alternatively, in some
embodiments, the media-playback device 102 operates to play media
content items stored locally on the media-playback device 102.
Further, in at least some embodiments, the media-playback device
102 operates to play media content items that are stored locally as
well as media content items provided by other systems.
In some embodiments, the media-playback device 102 is a computing
device, handheld entertainment device, smartphone, tablet, watch,
wearable device, or any other type of device capable of playing
media content. In yet other embodiments, the media-playback device
102 is a laptop computer, desktop computer, television, gaming
console, set-top box, network appliance, blue-ray or DVD player,
media player, stereo, or radio.
In at least some embodiments, the media-playback device 102
includes a location-determining device 150, a touch screen 152, a
processing device 154, a memory device 156, a content output device
158, a cadence-acquiring device 160, and a network access device
162. Other embodiments may include additional, different, or fewer
components. For example, some embodiments may include a recording
device such as a microphone or camera that operates to record audio
or video content. As another example, some embodiments do not
include one or more of the location-determining device 150 and the
touch screen 152.
The location-determining device 150 is a device that determines the
location of the media-playback device 102. In some embodiments, the
location-determining device 150 uses one or more of the following
technologies: Global Positioning System (GPS) technology which may
receive GPS signals 170 from satellites S, cellular triangulation
technology, network-based location identification technology,
WI-FI.RTM. positioning systems technology, and combinations
thereof.
The touch screen 152 operates to receive an input 172 from a
selector (e.g., a finger, stylus etc.) controlled by the user U. In
some embodiments, the touch screen 152 operates as both a display
device and a user input device. In some embodiments, the touch
screen 152 detects inputs based on one or both of touches and
near-touches. In some embodiments, the touch screen 152 displays a
user interface 164 for interacting with the media-playback device
102. As noted above, some embodiments do not include a touch screen
152. Some embodiments include a display device and one or more
separate user interface devices. Further, some embodiments do not
include a display device.
In some embodiments, the processing device 154 comprises one or
more central processing units (CPU). In other embodiments, the
processing device 154 additionally or alternatively includes one or
more digital signal processors, field-programmable gate arrays, or
other electronic circuits.
The memory device 156 operates to store data and instructions. In
some embodiments, the memory device 156 stores instructions for a
media-playback engine 166 that includes a tempo search control
engine 168. In some embodiments, the media-playback engine 166
operates to playback media content and the tempo search control
engine 168 operates to select media content for playback based on
various conditions, such as tempo. Additional details regarding the
tempo search control engine 168 are provided below.
The memory device 156 typically includes at least some form of
computer-readable media. Computer readable media includes any
available media that can be accessed by the media-playback device
102. By way of example, computer-readable media include computer
readable storage media and computer readable communication
media.
Computer readable storage media includes volatile and nonvolatile,
removable and non-removable media implemented in any device
configured to store information such as computer readable
instructions, data structures, program modules, or other data.
Computer readable storage media includes, but is not limited to,
random access memory, read only memory, electrically erasable
programmable read only memory, flash memory and other memory
technology, compact disc read only memory, blue ray discs, digital
versatile discs or other optical storage, magnetic cassettes,
magnetic tape, magnetic disk storage or other magnetic storage
devices, or any other medium that can be used to store the desired
information and that can be accessed by the media-playback device
102. In some embodiments, computer readable storage media is
non-transitory computer readable storage media.
Computer readable communication media typically embodies computer
readable instructions, data structures, program modules or other
data in a modulated data signal such as a carrier wave or other
transport mechanism and includes any information delivery media.
The term "modulated data signal" refers to a signal that has one or
more of its characteristics set or changed in such a manner as to
encode information in the signal. By way of example, computer
readable communication media includes wired media such as a wired
network or direct-wired connection, and wireless media such as
acoustic, radio frequency, infrared, and other wireless media.
Combinations of any of the above are also included within the scope
of computer readable media.
The content output device 158 operates to output media content. In
some embodiments, the content output device 158 generates media
output 110 for the user U. Examples of the content output device
158 include a speaker, an audio output jack, a BLUETOOTH.RTM.
transmitter, a display panel, and a video output jack. Other
embodiments are possible as well. For example, the content output
device 158 may transmit a signal through the audio output jack or
BLUETOOTH.RTM. transmitter that can be used to reproduce an audio
signal by a connected or paired device such as headphones or a
speaker.
The cadence-acquiring device 160 operates to acquire a cadence
associated with the user U. In at least some embodiments, the
cadence-acquiring device 160 operates to determine cadence directly
and includes one or more accelerometers or other motion-detecting
technologies. Alternatively, the cadence-acquiring device 160
operates to receive data representing a cadence associated with the
user U. For example, in some embodiments, the cadence-acquiring
device 160 operates to receive data from a watch, bracelet, foot
pod, chest strap, shoe insert, anklet, smart sock, bicycle
computer, exercise equipment (e.g., treadmill, rowing machine,
stationary cycle), or other device for determining or measuring
cadence. Further, in some embodiments, the cadence-acquiring device
160 operates to receive a cadence value input by the user U or
another person.
The network access device 162 operates to communicate with other
computing devices over one or more networks, such as the network
106. Examples of the network access device include wired network
interfaces and wireless network interfaces. Wireless network
interfaces includes infrared, BLUETOOTH.RTM. wireless technology,
802.11a/b/g/n/ac, and cellular or other radio frequency interfaces
in at least some possible embodiments.
The network 106 is an electronic communication network that
facilitates communication between the media-playback device 102 and
the media-delivery system 104. An electronic communication network
includes a set of computing devices and links between the computing
devices. The computing devices in the network use the links to
enable communication among the computing devices in the network.
The network 106 can include routers, switches, mobile access
points, bridges, hubs, intrusion detection devices, storage
devices, standalone server devices, blade server devices, sensors,
desktop computers, firewall devices, laptop computers, handheld
computers, mobile telephones, and other types of computing
devices.
In various embodiments, the network 106 includes various types of
links. For example, the network 106 can include wired and/or
wireless links, including BLUETOOTH.RTM., ultra-wideband (UWB),
802.11, ZIGBEE.RTM., cellular, and other types of wireless links.
Furthermore, in various embodiments, the network 106 is implemented
at various scales. For example, the network 106 can be implemented
as one or more local area networks (LANs), metropolitan area
networks, subnets, wide area networks (such as the Internet), or
can be implemented at another scale. Further, in some embodiments,
the network 106 includes multiple networks, which may be of the
same type or of multiple different types.
The media-delivery system 104 comprises one or more computing
devices and operates to provide media content items to the
media-playback devices 102 and, in some embodiments, other
media-playback devices as well. The media-delivery system 104
includes a media server 180 and a repetitive-motion activity server
182. In at least some embodiments, the media server 180 and the
repetitive-motion activity server 182 are provided by separate
computing devices. In other embodiments, the media server 180 and
the repetitive-motion activity server 182 are provided by the same
computing devices. Further, in some embodiments, one or both of the
media server 180 and the repetitive-motion activity server 182 are
provided by multiple computing devices. For example, the media
server 180 and the repetitive-motion activity server 182 may be
provided by multiple redundant servers located in multiple
geographic locations.
The media server 180 operates to transmit stream media 218 to
media-playback devices such as the media-playback device 102. In
some embodiments, the media server 180 includes a media server
application 184, a processing device 186, a memory device 188, and
a network access device 190. The processing device 186, memory
device 188, and network access device 190 may be similar to the
processing device 154, memory device 156, and network access device
162 respectively, which have each been previously described.
In some embodiments, the media server application 184 operates to
stream music or other audio, video, or other forms of media
content. The media server application 184 includes a media stream
service 194, a media data store 196, and a media application
interface 198. The media stream service 194 operates to buffer
media content such as media content items 206, 208, and 210, for
streaming to one or more streams 200, 202, and 204.
The media application interface 198 can receive requests or other
communication from media-playback devices or other systems, to
retrieve media content items from the media server 180. For
example, in FIG. 2, the media application interface 198 receives
communication 234 from the media-playback engine 166.
In some embodiments, the media data store 196 stores media content
items 212, media content metadata 214, and playlists 216. The media
data store 196 may comprise one or more databases and file systems.
Other embodiments are possible as well. As noted above, the media
content items 212 may be audio, video, or any other type of media
content, which may be stored in any format for storing media
content.
The media content metadata 214 operates to provide various
information associated with the media content items 212. In some
embodiments, the media content metadata 214 includes one or more of
title, artist name, album name, length, genre, mood, era, etc. The
playlists 216 operate to identify one or more of the media content
items 212 and. In some embodiments, the playlists 216 identify a
group of the media content items 212 in a particular order. In
other embodiments, the playlists 216 merely identify a group of the
media content items 212 without specifying a particular order.
Some, but not necessarily all, of the media content items 212
included in a particular one of the playlists 216 are associated
with a common characteristic such as a common genre, mood, or
era.
The repetitive-motion activity server 182 operates to provide
repetitive-motion activity-specific information about media content
items to media-playback devices. In some embodiments, the
repetitive-motion activity server 182 includes a repetitive-motion
activity server application 220, a processing device 222, a memory
device 224, and a network access device 226. The processing device
222, memory device 224, and network access device 226 may be
similar to the processing device 154, memory device 156, and
network access device 162 respectively, which have each been
previously described.
In some embodiments, repetitive-motion activity server application
220 operates to transmit information about the suitability of one
or more media content items for playback during a particular
repetitive-motion activity. The repetitive-motion activity server
application 220 includes a repetitive-motion activity interface 228
and a repetitive-motion activity media metadata store 230.
In some embodiments, the repetitive-motion activity server
application 220 may provide a list of media content items at a
particular tempo to a media-playback device in response to a
request that includes a particular cadence value. Further, in some
embodiments, the media content items included in the returned list
will be particularly relevant for the repetitive motion activity in
which the user is engaged (for example, if the user is running, the
returned list of media content items may include only media content
items that have been identified as being highly runnable).
The repetitive-motion activity interface 228 operates to receive
requests or other communication from media-playback devices or
other systems to retrieve information about media content items
from the repetitive-motion activity server 182. For example, in
FIG. 2, the repetitive-motion activity interface 228 receives
communication 236 from the media-playback engine 166.
In some embodiments, the repetitive-motion activity media metadata
store 230 stores repetitive-motion activity media metadata 232. The
repetitive-motion activity media metadata store 230 may comprise
one or more databases and file systems. Other embodiments are
possible as well.
The repetitive-motion activity media metadata 232 operates to
provide various information associated with media content items,
such as the media content items 212. In some embodiments, the
repetitive-motion activity media metadata 232 provides information
that may be useful for selecting media content items for playback
during a repetitive-motion activity. For example, in some
embodiments, the repetitive-motion activity media metadata 232
stores runnability scores for media content items that correspond
to the suitability of particular media content items for playback
during running. As another example, in some embodiments, the
repetitive-motion activity media metadata 232 stores timestamps
(e.g., start and end points) that identify portions of a media
content items that are particularly well-suited for playback during
running (or another repetitive-motion activity).
Each of the media-playback device 102 and the media-delivery system
104 can include additional physical computer or hardware resources.
In at least some embodiments, the media-playback device 102
communicates with the media-delivery system 104 via the network
106.
Although in FIG. 2 only a single media-playback device 102 and
media-delivery system 104 are shown, in accordance with some
embodiments, the media-delivery system 104 can support the
simultaneous use of multiple media-playback devices, and the
media-playback device can simultaneously access media content from
multiple media-delivery systems. Additionally, although FIG. 2
illustrates a streaming media based system for cadence
determination and media content selection, other embodiments are
possible as well. For example, in some embodiments, the
media-playback device 102 includes a media data store 196 and the
media-playback device 102 is configured to perform cadence
determination and media content selection without accessing the
media-delivery system 104. Further in some embodiments, the
media-playback device 102 operates to store previously streamed
media content items in a local media data store.
In at least some embodiments, the media-delivery system 104 can be
used to stream, progressively download, or otherwise communicate
music, other audio, video, or other forms of media content items to
the media-playback device 102 based on a cadence acquired by the
cadence-acquiring device 160 of the media-playback device 102. In
accordance with an embodiment, a user U can direct the input 172 to
the user interface 164 to issue requests, for example, to playback
media content corresponding to the cadence of a repetitive motion
activity on the media-playback device 102.
FIG. 3 illustrates an example method 250 of selecting media content
played by the media-playback device 102 based upon a tempo of the
media content. Such a method can be used, for example, when the
user is engaged repetitive motion activities, such as running or
walking. Media content, such as music, can impact the performance
of such activities. For example, as noted above, music of a faster
tempo can encourage the user U to run at a faster cadence and vice
versa.
At the step 252 of the method 250, the tempo search control engine
168 of the media-playback device 102 receives a selection of media
content. This selection can take a variety of forms.
For example, the user U can simply identify certain media content
of a desired tempo. In another example, the user can identify a
desired tempo itself (e.g., 90 beats per minute), as shown in FIG.
7 and described further below.
In yet other examples, one or more automated processes can be used
to select certain media content and/or tempo. For example, various
attributes of the user, such as the user's physiological state, can
be used as an automated process for selecting a desired tempo. An
example of such processes are described in U.S. Patent Application
Ser. No. 62/163,915, titled HEART RATE CONTROL BASED UPON MEDIA
CONTENT SELECTION, filed on May 19, 2015, the entirety of which is
hereby incorporated by reference. This patent application describes
how physiological measurements, such as heart rate, and
non-physiological measurements, such as location, can be used to
automatically select a desired tempo for the user U.
Next, at step 254, the selected media content is analyzed to
identify a relevant tempo. Various processes can be used to analyze
media content, such as music, to determine a tempo. See FIG. 4 for
more details.
Finally, at step 256, additional media content meeting the desired
tempo requirements are provided to the user, such as in a graphical
user interface. One example of such a user interface is described
with reference to FIG. 7 below. Other examples are provided in U.S.
Patent Application Ser. No. 62/163,887, titled MULTI-TRACK PLAYBACK
OF MEDIA CONTENT DURING REPETITIVE MOTION ACTIVITIES, filed on May
19, 2015, the entirety of which is hereby incorporated by
reference. In that patent application, a grid interface is
disclosed that allows media content of a particular
In one context, the steps 254, 256 are performed by the
media-delivery system 104 in response to a request from the tempo
search control engine 168. For example, the tempo search control
engine 168 can receive an indication of a desired tempo (either
through selected media content or a specified tempo), and the
media-delivery system 104 is configured to perform the steps 254,
256 and deliver media content of the desired tempo back to the
media-playback device 102 for consumption by the user U.
FIG. 4 illustrates more details about the step 254 of FIG. 3, in
which media content is analyzed to identify tempo. As noted, the
media-delivery system 104 can perform the step 254 based upon a
request from the media-playback device 102.
At step 262, the relevant tempo is identified. In this context, the
media content provided by the user U is analyzed to determine the
tempo of the media content. This process is described below.
As noted, in other examples, the user can simply select a desired
tempo instead of providing media content, or a tempo can
automatically be provided based upon analysis of such criteria as
physiological aspects of the user U, like heart rate.
Next, at step 264, the media content in the media server
application 184 is filtered based upon certain criteria. In one
example, each media content item stored by the media server
application 184 is analyzed and particular additional metadata for
each item is stored by the media content metadata 214.
This metadata may include such information as a tempo for the media
content item. In one example, each media content item is analyzed,
and a tempo is associated with the metadata for the item.
A tempo of a media content item can be determined in various known
manners. In the example of songs, a tempo of a song can be
relatively easily identified because songs typically have a steady
tempo throughout their entire playing time. Where a tempo changes
significantly throughout a song, in some embodiments, such
variations in tempo can be averaged to represent a single tempo of
the song. In other examples, a portion of the song having an
approximately constant tempo can be identified, and such a constant
tempo can be used as a tempo for the entire song. In yet other
examples, the portion of the song having an approximately constant
tempo is taken and used to replace the entire song while the other
portion of the song, which has variable tempo, are excluded from
playback. Other methods of obtaining a tempo of a song are also
possible.
Additional details on determining a tempo for media content is
provided in U.S. Patent Application Ser. No. 62/163,845, titled
CADENCE-BASED PLAYLISTS MANAGEMENT SYSTEM, filed on May 19, 2015,
the entirety of which is hereby incorporated by reference.
The metadata may also include other criteria, such as a runnability
score for each media content item. A runnability score can be
calculated based upon a variety of methods and factors, such as
comparison to other content known to have desired characteristics
or properties that are suitable for running. For example, the
runnability scores can be calculated based on beat strength and
tempo regularity of audio signals of the media content items.
Additional details regarding how a runnability score can be
calculated for a media content item are provided in U.S. Patent
Application Ser. No. 62/163,921, titled IDENTIFYING MEDIA CONTENT,
filed on May 19, 2015, the entirety of which is hereby incorporated
by reference, and discussed in further detail herein with reference
to FIGS. 8 and 9.
Additional details on the filtering of the step 264 are provided
with reference to FIG. 5.
Finally, at step 266, filtered media content items having the
desired tempo are selected. Additional details on this process are
provided with reference to FIG. 6.
At FIG. 5, the filtering of the media content of the step 264 is
described in more detail.
At step 272, the runnability score for a particular media content
item is determined. This can be accomplished using the processes
described above. In some embodiments, the runnability score is a
value that corresponds to how similar a media content item is to
the positive training examples as calculated using the runnability
model. In some embodiments, the runnability score is a numerical
value in the range of 0-1 in which higher values indicate the media
content item is more similar to the positive training examples than
a lower value. Alternatively, the runnability score may be stored
as part of the metadata associated with the media content item.
Next, at step 274, a determination is made regarding whether or not
the user previously rated the particular media content item. For
example, as described further below, the user U can rate a
particular media content item as one the user likes or dislikes. If
the user has previously liked the particular media content item,
control is passed to step 276, and a decreased threshold filter is
used. Otherwise, control is passed to step 278, and a standard
filter threshold is used.
For example, if the user has previously "liked" the particular
media content item, the decreased threshold filter may require that
the runnability score for the media content item be at least 0.4.
Alternatively, if the media content item has not been previously
rated, the standard threshold filter may require that the
runnability score for the media content item be at least 0.6. In
this manner, media content items that were previously marked as
"liked" are favored.
Next, at step 280, the relevant filter (i.e., decreased or standard
threshold) is applied. If the media content item exceeds the
threshold of the applied filter, control is passed to step 282, and
the media content item is recommended to the user. Otherwise,
control is passed to step 284, and the media content item is not
recommended.
Referring now to FIG. 6, additional details are provided about the
step 266 of filtering the media content based upon tempo.
At step 290, a desired tempo range is determined. This range is
based upon the desired tempo that is either calculated from the
media content selected by the user, the tempo that is specifically
selected by the user, and/or by one or more automated processes of
determining a desired tempo, such as by an analysis of heart rate,
as described above.
The desired tempo is converted to a range of tempos, as is noted
above. In some examples, this range can have various scales, such
as 2 beats, 5 beats, 10 beats, etc. For example, if the desired
tempo is 178, that tempo is converted to a range of 175-180.
In another example, the system is programmed to define a target
number of songs to return, such as 5, 10, 15, 20, 50 100. For
instance, if the target is to return 10 songs around 178 BPM, and
given the number of songs available around that tempo, the
resolution or range for the tempo can be modified, such as low as
+/-0.5 BPM or a large as +/-7 BPM. The dynamic range is dependent
on the size of the portfolio of media content, which can be driven
by such factors as how the runnability scores are calculated. In
other examples, the songs are simply ranks based upon how far each
song is from the desired tempo, and the desired number of songs is
selected based upon that ranking. In other instances, the range to
find desired content is dynamically calculated based upon multiple
factors, such as size of portfolio and runnability.
This range is then used at step 292 to filter the media content.
Specifically, the tempo of each media content item is analyzed to
determine if the tempo falls within the range. As noted above, each
media content item may include metadata defining the tempo for that
media content item. The tempo metadata can be used to determine if
the media content item falls within the desired tempo range.
The media content falling within the desired range is then analyzed
at step 294 to determine if sufficient media content has been
identified. For example, if the range is a tempo of 175-180 beats
per minute, perhaps 1000 songs fall within that range. In such an
instance, a sufficient amount of media content has been identified,
and control is provided to step 296, where the process
continues.
However, if the number of media content items with the desired
tempo is small, such as less than 100, less than 50, less than 20,
less than 10, and/or less than 5, control can instead be passed to
step 298, and the filtering of the content media can be
modified.
One possible modification is to expand the range of tempos. In the
example, the range could be expanded to be 170-185 in order to
attempt to capture more media content items. In another example,
other thresholds, such as the thresholds associated with the
runnability scores used in the step 264 can be loosened. In yet
another example, the tempo ranges can be halved or doubled (as
noted above), which can result in tempos that provide similar
guidance when running. Other configurations are possible.
Once the filters have been modified, control is passed back to the
step 290 and the step 266 of filtering the media content based upon
tempo is performed again with the modified filters.
Although filtering based upon criteria such as runnability and
tempo are provided in the examples, other criteria can also be used
to filter the media content. Examples of other criteria include the
strength of the beat, the general energy of the content, the
similarity of the content to other items. Other filtering based
upon such criteria as desired genre, mood, or age (i.e., era) can
also be used.
Referring now to FIG. 7, an example tempo-based content playback
screen 400 displayed by some embodiments of the user interface 164
of the media-playback device 102 is shown. In some embodiments, the
tempo-based content playback screen 400 is displayed in response to
receiving a request by the user to select media content of a
desired tempo.
In some embodiments, the tempo-based content playback screen 400
includes a playlist information message 402, a previous media
content item display panel 404, a current media content item
display panel 406, a next media content item display panel 408, a
current media content item information message 410, a dislike
control 412, a like control 414, a tempo information message 416,
and a pause control 418.
The playlist information message 402 operates to display
information about the currently playing playlist of media content
items. The playlist may be a pre-defined playlist of media content
items that correspond to an acquired cadence or an ad-hoc playlist
generated by the media-playback device 102 or the media-delivery
system 104 based on the acquired cadence. In some embodiments, the
playlist information message 402 displays a title provided with a
pre-defined playlist (e.g. "Outdoor Running," "Spin Class," "Peak
Performance," etc.). In some embodiments, the playlist information
message 402 displays information that relates to the media content
items included in an ad-hoc playlist such as a region (e.g.,
Sweden, Europe, U.S., etc.), a genre (e.g., Country, Rock, Rap,
etc.), a mood (e.g., calm, happy, etc.), an era (e.g., 70's, 80's,
90's, 00's, etc.), or popularity (e.g., Top 50, etc.).
The previous media content item display panel 404 operates to
display information about the previously played media content item
such as an image associated with the previously played media
content item (e.g., an album cover, an artist photograph, etc.).
The current media content item display panel 406 and the next media
content item display panel 408 operate similarly with respect to
the currently playing media content item and the media content item
that is schedule to play next. In some embodiments, the user
interface 164 operates to cause the next or previous media content
item to begin playback in response to detecting a swipe input to
the left or right over the current media content item display panel
406. Additionally, in some embodiments, the user interface 164
operates to cause the previously played media content item to begin
playback in response to detecting a touch input on the previous
media content item display panel 404. Similarly, in some
embodiments, the user interface 164 operates to cause the next
media content item to begin playback in response to detecting a
touch input on the next media content item display panel 408.
The current media content item information message 410 operates to
display information about the currently playing media content item.
Some embodiments display one or more of the following: a title, an
artist name, an album name, a current position, a total length, and
a tempo.
The dislike control 412 and the like control 414 operate to receive
inputs indicating that a user dislikes or likes the currently
playing media content item. In some embodiments, the media-playback
device stores a like/dislike value associated with the currently
playing media content item upon actuation of either the dislike
control 412 or the like control 414. The value may be stored
locally on the media-playback device 102 or remotely on the
media-delivery system 104 or elsewhere. In some embodiments, one or
both of the media-playback device 102 and the media-delivery system
104 use the like/dislike values that have been previously stored in
selecting media content items for future playback. Additionally, in
at least some embodiments, upon actuation of the dislike control
412, the currently playing media content item stops playing
immediately or after a period of time and a new media content item
begins to play.
The tempo information message 416 operates to present information
to the user about the tempo of the current media content item. In
some embodiments, the tempo information message 416 displays a
numeric value representing the user U's current tempo
selection.
As noted, in some embodiments, the user can select a particular
desired tempo manually. In such an example, the user can select the
tempo information message 416 to bring up increase/decrease tempo
arrows and/or a keypad that allows the user to directly input a
desired tempo. Once the desired tempo is inputted by the user, the
system can provide media content and/or samples at the desired
tempo for the user.
Additionally, in some embodiments, the tempo information message
416 also presents information related to whether the tempo has
recently changed. For example, the tempo information message 416
may include an arrow pointing up if the tempo has recently
increased and an arrow pointing down if the tempo has recently
decreased.
Alternatively, the tempo may be displayed in a first color to
indicate a recent increase, a second color to indicate a recent
decrease, and a third color to indicate a stable tempo. As yet
another alternative, the tempo information message 416 may blink or
otherwise indicate the occurrence of a recent change in tempo. In
yet another embodiment, the tempo information message 416 may
operate to indicate how a current tempo compares to a goal or
target cadence using any of the previously mentioned visual
indicators.
In yet other examples, information in addition to or other than
tempo can be displayed. For example, the information message 416
can be configured to display the user U's heart rate. In yet
another example, the information message 416 can be configured to
display an estimated cadence, as described in U.S. Patent
Application Ser. No. 62/163,840, titled CADENCE DETERMINATION AND
MEDIA CONTENT SELECTION, filed on May 19, 2015, the entirety of
which is hereby incorporated by reference.
The pause control 418 operates to receive a pause input from the
user. In some embodiments, the pause input triggers the
media-playback device 102 to pause cadence acquisition.
Beneficially, by pausing cadence acquisition, the user can take a
break or otherwise change cadence without causing the playback of
media content items to change. Users may take break for many
reasons, such as to rest/recover, to wait to safely cross an
intersection, or to wait for a running partner. Users may
temporarily change cadence for many reasons as well such as to
climb a stair case or a big hill, to cross rugged terrain, to weave
through heavy traffic, etc. Additionally, in some embodiments, the
pause input also triggers the media-playback device 102 to pause
playback of the media content items.
FIG. 8 illustrates an example method 310 of acquiring a list of
positive examples of runnable media content items. Such a method
can be used, for example, to identify media content items as
runnable based on the playlists users have created.
At operation 312, playlists that appear related to running are
identified as source playlists. The playlists may be identified by
analyzing the playlists 216. In some embodiments, source playlists
are identified based on the inclusion of certain words or phrases
in a title or description associated with the playlist. For
example, words that are related to running (e.g., run, running,
jog, marathon, 5 k, etc.) may be used to identify source playlists.
Additionally, in some embodiments, words that relate to fitness
(work out, health club, training, etc.) are also used to identify
source playlists. Furthermore, in some embodiments, words that
relate to other types of repetitive-motion activities are also used
to identify source playlists.
At operation 314, a list of potential example media content items
is generated based on the source playlists. In some embodiments,
all media content items appearing in at least a predetermined
number of play lists are included in the list. In embodiments, the
predetermined number is 1, 2, 5, 10, 50, 100, 500, or another
number.
Further some embodiments, analyze the source playlists to further
determine the relevance of the play list to running. The analysis
may be based on many factors including the words that were used to
identify the source playlist, whether the words appeared in a title
or a description, the curator of the play list, the number of users
that follow the playlist, the number of times the playlist has been
played, etc. In some embodiments, a weighting scheme is used to
calculate a weight value for the source playlists. Example
weighting schemes used in some embodiment include: weighting a
playlist that includes words associated with running higher than a
playlist that includes words associated with fitness or another
repetitive-motion activity; weighting a playlist that includes a
relevant word in a title higher than a playlist that includes a
relevant word in a description; weighting a play list curated by a
streaming service (or professional curator) higher than a playlist
curated by a user (or vice versa); weighting a playlist with more
followers higher than a playlist with fewer followers; weighting a
playlist that has been played more times higher than a playlist
that has been played fewer times. In some embodiments, the weighted
values of the source play list that include a particular potential
example media content item are summed (or otherwise combined) and
the resulting value (referred to as a positive playlist inclusion
score herein) is compared to a predetermined threshold. The
potential example media content items with a positive playlist
inclusion score that exceeds the threshold may be analyzed further
as described below.
At operation 316, it is determined whether the potential example
media content items are included in playlists that appear
inappropriate for running. In some embodiments, playlists are
identified as inappropriate for running based on the inclusion of
words or phrases in a title that are related to relaxing (e.g.,
calming, chill, relax, wind down, sleep, calm, etc.). In some
embodiments, a negative playlist inclusion score is calculated for
the potential example media content items based on being included
in playlists that are identified as not being appropriate for
running. The negative playlist inclusion score for a potential
example media content item is calculated in a similar manner and
according to similar factors as the positive playlist inclusion
score.
At operation 318, a combined playlist inclusion score is calculated
for the potential example media content items included in the list
based on the playlists in which the potential example media content
items are included. In some embodiments, the combined playlist
inclusion score is calculated as a ratio of the positive playlist
inclusion score to the negative playlist inclusion score. In other
embodiments, the combined playlist inclusion score is calculated
otherwise, such as by calculating a difference between the positive
playlist inclusion score and the negative playlist inclusion score.
Further, in some embodiments, the combined playlist inclusion score
is calculated as a difference between or ratio of the number of
play lists that appear related to running and the number of play
lists that appear inappropriate for running in which the media
content item is included.
At operation 320, potential example media content items are
selected as positive example media content items based upon the
combined playlist inclusion score In some embodiments, potential
example media content items that have a combined playlist inclusion
score exceeding a predetermined threshold are selected as positive
examples of runnable media content items. As an example, when the
combined playlist inclusion score is calculated as a ratio, the
predetermined threshold is two, three, four, five, or ten in some
embodiments. Other embodiments use a predetermined threshold in a
range of one to twenty-five. Additionally, in some embodiments, a
predetermined number of media content items having the highest
combined play list inclusion scores are selected as positive
examples.
FIG. 9 illustrates an example method 350 of building a runnability
model based on positive examples of runnable media content items.
Such a method can be used, for example, to build a model for
classifying or identifying additional media content items as
runnable.
At operation 352, characteristics of the audio signals of the
positive examples of runnable media content items are determined.
In some embodiments, the audio signals of the positive examples are
analyzed to determine the characteristics. Additionally, in some
embodiments, some or all of the characteristics of the audio
signals are retrieved from the media content metadata 214 or
elsewhere.
Example characteristics determined by some embodiments include an
average duration of a musical event such as a single note or other
musical event, a tempo regularity, a percussivity, and a beat
strength. In some embodiments, the average duration of a musical
event is calculated in various ways, including by dividing a total
number of musical events in a media content item by a duration of
the media content item. The tempo regularity corresponds to the
consistency of the beat in a media content item. In some
embodiments, the tempo regularity is based on calculating a
standard deviation or variance value for measurements of the tempo
over multiple intervals of a media content item. The percussivity
corresponds to the strength or contribution of percussive
instruments (or synthesize equivalents) to the media content item.
The beat strength is proportional to the loudness of musical events
that happen in correspondence to a beat. Some embodiments also
include characteristics that are determined by other machine
learning models. For example, some embodiments, include an energy
characteristic that is calculated by a machine learning model
trained to rate the relative energy levels of various media content
items similarly to a user's rating. Other embodiments determine
additional, different, or fewer characteristics.
At operation 354, the determined characteristics are used to build
a statistical model that relates the determined characteristics to
a similarity value to the positive examples. In some embodiments,
the model is a function or equation that operates on the values of
the various characteristics to calculate a value corresponding to
the similarity to the positive examples. In some embodiments, the
model represents each characteristic as a dimension in a
multi-dimensional space. Further, in some embodiments, the model
defines an equation to compute the likelihood of a media content
item being similar to the positive examples as far as the modeled
characteristics are concerned.
As noted previously, although many of the examples provided above
are described with respect to running, other embodiments relate to
other repetitive motion activities as well such as cycling,
swimming, and rowing.
The various embodiments described above are provided by way of
illustration only and should not be construed to limit the claims
attached hereto. Those skilled in the art will readily recognize
various modifications and changes that may be made without
following the example embodiments and applications illustrated and
described herein, and without departing from the true spirit and
scope of the following disclosure.
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